ConflictSync: Bandwidth Efficient Synchronization of Divergent State

TL;DR

ConflictSync introduces a novel digest-driven synchronization method for state-based CRDTs, significantly reducing data transfer and improving efficiency in distributed systems by leveraging advanced set reconciliation techniques.

Contribution

It presents the first digest-driven synchronization algorithm for CRDTs, generalizing set reconciliation with Bloom filters and rateless codes to optimize bandwidth usage.

Findings

Reduces total data transfer by up to 18 times.

Bloom filter prefiltering cuts overhead by 50%.

Effective across various similarity levels and applicable to diverse distributed data models.

Abstract

State-based Conflict-free Replicated Data Types (CRDTs) are widely used in distributed systems to ensure high availability without coordination. However, their naive synchronization strategy - transmitting the full state - incurs high communication costs. Existing optimizations like delta-CRDTs reduce this overhead but rely on external metadata that must be garbage collected to prevent unbounded growth, at the cost of full state transmissions after network partitions. This paper presents ConflictSync, the first digest-driven synchronization algorithm for state-based CRDTs. We reduce synchronization to the set reconciliation of irredundant join decompositions and build on existing work in rateless set reconciliation. To support CRDTs, we generalize set reconciliation to variable-sized elements, and further introduce a novel combination of Bloom filters with Rateless Invertible Bloom Lookup Tables to address inefficiencies at low similarity levels. Our evaluation shows that ConflictSync reduces total data transfer by up to 18 times compared to traditional state-based synchronization. Bloom filter prefiltering reduces overhead by up to 50% compared to pure rateless reconciliation at 0% similarity, while pure rateless reconciliation performs better above 93% similarity. We characterize the trade-off between similarity level and Bloom filter size, identifying optimal configurations for different synchronization scenarios. Although developed for CRDTs, ConflictSync applies to any synchronization problem where states can be decomposed into sets of constituent components, analogous to join decompositions, making it suitable for a wide range of distributed data models.